danbooru_metadata / scripts /update_danbooru.py
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fix(sync): let the post sync finish, and land the pages still in flight
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import argparse
import queue
import threading
import time
from pathlib import Path
from time import sleep
import requests
from _danbooru import DEFAULT_RATE, RateLimiter, get_json
from _env import credentials
from _paths import DANBOORU_DB_PATH
from rich.progress import (
BarColumn,
Progress,
TextColumn,
TimeElapsedColumn,
TimeRemainingColumn,
)
from sqlalchemy import text
from db import get_engine, t_posts
url_queue: queue.Queue[str | None] = queue.Queue(maxsize=64)
data_queue: queue.Queue[list[dict[str, object]] | None] = queue.Queue(maxsize=64)
# 彻底抓不到的页。list.append 在 CPython 下是原子的,worker 线程可以直接写。
failures: list[str] = []
parser = argparse.ArgumentParser()
parser.add_argument("--start_id", type=int, default=0)
parser.add_argument("--api_key", type=str)
parser.add_argument("--login", type=str)
parser.add_argument("--workers", type=int, default=16)
parser.add_argument(
"--rate",
type=float,
default=DEFAULT_RATE,
help=f"起步请求速率(req/s,默认 {DEFAULT_RATE},全部 worker 共享)。撞到 429 会自动减半再慢慢恢复。",
)
parser.add_argument("--db_path", type=str, default=str(DANBOORU_DB_PATH))
parser.add_argument(
"--follow",
action="store_true",
help="追平后不退出,每 2 秒轮询新帖。默认追平即退出 —— 定时任务链需要这个脚本会结束。",
)
parser.add_argument(
"--update",
action="store_true",
help="全量更新模式:从头遍历所有 id 刷新 score/fav_count 等变化的数值,"
"而非仅抓取新帖。已消失的条目会保留原值,不会从数据库删除。",
)
args = parser.parse_args()
API_KEY, LOGIN = credentials(args.api_key, args.login)
# 一个发牌器管住所有 worker。限速是按账号算的,16 个线程各自限速等于超发 16 倍。
limiter = RateLimiter(args.rate)
# 只回显 login。匿名和已认证的限流差一个数量级,跑之前得能一眼看出走的哪条路。
print(f"syncing posts -- {f'authenticated as {LOGIN}' if LOGIN else 'anonymous (heavier rate limiting)'}")
BASE_API_URL = "https://danbooru.donmai.us/posts.json?page=a{}&limit=200{}"
LATEST_ID_URL = "https://danbooru.donmai.us/posts.json?limit=1{}"
latest_id = 1
def auth_query() -> str:
# 仅在提供凭据时附加认证参数,否则匿名访问;拼接 api_key=None 会触发 401
if API_KEY and LOGIN:
return f"&api_key={API_KEY}&login={LOGIN}"
return ""
def fetch_latest_id(session: requests.Session) -> None:
global latest_id
try:
rows = get_json(session, LATEST_ID_URL.format(auth_query()), limiter=limiter)
except RuntimeError as exc:
# 只是进度条的上界,拿不到就沿用旧值继续跑,不值得为它中断同步。
print(f"\ncould not refresh the latest id ({exc}); keeping {latest_id}")
return
if rows and "id" in rows[0]:
latest_id = int(rows[0]["id"])
def update_latest_id() -> None:
session = requests.Session()
while True:
fetch_latest_id(session)
time.sleep(60)
def fetch_data() -> None:
session = requests.Session()
while True:
url = url_queue.get()
if url is None:
url_queue.task_done()
break
try:
data_queue.put(get_json(session, url, limiter=limiter))
except RuntimeError as exc:
# 记下来,不要跳过就算了。这一页是 200 条投稿,少了在成品里完全看不出来,
# 而增量模式下次从数据库最大 id 起跑,永远不会回头补这个洞。
failures.append(f"{url}: {exc}")
print(f"\nGAVE UP on {url}: {exc}")
url_queue.task_done()
def save_data(engine_path: str, required_columns: list[str]) -> None:
engine = get_engine(engine_path)
while True:
data = data_queue.get()
if data is None:
data_queue.task_done()
break
for column in required_columns:
for row in data:
if column not in row:
row[column] = None
with engine.connect() as conn:
conn.execute(t_posts.insert().prefix_with("OR REPLACE"), data)
conn.commit()
data_queue.task_done()
def drain(workers: list[threading.Thread]) -> None:
"""让在途的页真正落盘,再退出。
这些线程是 daemon,进程一退就地消失。生产者停下时队列里通常还压着几十页 ——
直接返回等于把它们扔掉,而且扔得悄无声息:日志上看是一次干净的同步,数据库里
少了几千条。所以按 抓取 -> 保存 的顺序逐级投毒丸,每级都等它自己排空。
"""
for _ in workers:
url_queue.put(None)
for worker in workers:
worker.join()
data_queue.put(None)
data_queue.join()
def main() -> None:
engine_path = Path(args.db_path)
if engine_path.parent != Path("."):
engine_path.parent.mkdir(parents=True, exist_ok=True)
threads: list[threading.Thread] = []
for _ in range(args.workers):
thread = threading.Thread(target=fetch_data, daemon=True)
thread.start()
threads.append(thread)
# 先同步取一次,再决定要不要开轮询线程。latest_id 初值是 1,交给后台线程去填
# 就有竞态:非 follow 模式下 current_id(约 1190 万) >= 1 立刻成立,一条不抓就退出。
fetch_latest_id(requests.Session())
if args.follow:
# 只有常驻模式才需要它。一次性同步对着固定快照跑,结果可复现。
threading.Thread(target=update_latest_id, daemon=True).start()
required_columns = [col.name for col in t_posts.columns if not col.primary_key]
danbooru_engine = get_engine(str(engine_path))
t_posts.metadata.create_all(danbooru_engine, tables=[t_posts])
with danbooru_engine.connect() as conn:
res = conn.execute(text("SELECT MAX(id) FROM posts"))
row = res.fetchone()
latest_db_id = row[0] if row and row[0] else 1
# 起点优先级:显式 --start_id(续传) > --update(从头全量刷新) > 增量(数据库最大 id)
if args.start_id != 0:
start_id = args.start_id
elif args.update:
start_id = 1
else:
start_id = latest_db_id
print("mode:", "update" if args.update else "incremental")
print("start_id:", start_id)
save_thread = threading.Thread(
target=save_data,
args=(str(engine_path), required_columns),
daemon=True,
)
save_thread.start()
try:
with Progress(
TextColumn("[progress.description]{task.description}"),
BarColumn(),
TextColumn("[progress.percentage]{task.percentage:>3.0f}%"),
TimeElapsedColumn(),
TimeRemainingColumn(),
TextColumn("[{task.completed} / {task.total}]"),
) as progress:
total_items = max(latest_id - start_id + 1, 0)
task = progress.add_task("Processing", start=True, total=total_items)
current_id = start_id
while True:
if current_id >= latest_id:
progress.update(task, completed=latest_id)
if not args.follow:
break
sleep(2)
continue
url = BASE_API_URL.format(current_id, auth_query())
# 不在这里 sleep:队列 maxsize=64 已经是背压,真正的节奏由 limiter
# 决定。producer 再睡一次只会和 limiter 叠加成一个谁也说不清的速率。
url_queue.put(url)
current_id += 200
progress.update(task, completed=current_id, total=latest_id)
except KeyboardInterrupt:
print("Stopped by user")
drain(threads)
with danbooru_engine.connect() as conn:
rows = conn.execute(text("SELECT COUNT(*) FROM posts")).scalar()
newest = conn.execute(text("SELECT MAX(id) FROM posts")).scalar()
print(f"posts: {rows:,} rows, max id {newest:,} (site was at {latest_id:,})")
print(f"final rate: {limiter.rate:.2f} req/s (started at {args.rate:g})")
if failures:
# 非零退出码:定时任务链上游得知道这次存档是有洞的。
print(f"\n{len(failures)} page(s) were never fetched -- the archive has holes:")
for failure in failures[:20]:
print(f" {failure}")
if len(failures) > 20:
print(f" ... and {len(failures) - 20} more")
print("Re-run with --start_id set below the lowest missing id to fill them.")
raise SystemExit(1)
raise SystemExit(0)
if __name__ == "__main__":
main()